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Automatic hoof-on a...
Automatic hoof-on and -off detection in horses using hoof-mounted inertial measurement unit sensors
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- Hernlund, Elin (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för anatomi, fysiologi och biokemi,Department of Anatomy, Physiology and Biochemistry (AFB)
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- Rhodin, Marie (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för anatomi, fysiologi och biokemi,Department of Anatomy, Physiology and Biochemistry (AFB)
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(creator_code:org_t)
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- Public Library of Science (PLoS), 2020
- 2020
- Engelska.
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15
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Abstract
Ämnesord
Stäng
- For gait classification, hoof-on and hoof-off events are fundamental locomotion characteristics of interest. These events can be measured with inertial measurement units (IMUs) which measure the acceleration and angular velocity in three directions. The aim of this study was to present two algorithms for automatic detection of hoof-events from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. Seven Warmblood horses were equipped with two wireless IMUs, which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted on a lead over a force plate for internal validation. The agreement between the algorithms for the acceleration and angular velocity signals with the force plate was evaluated by Bland Altman analysis and linear mixed model analysis. These analyses were performed for both hoof-on and hoof-off detection and for both algorithms separately. For the hoof-on detection, the angular velocity algorithm was the most accurate with an accuracy between 2.39 and 12.22 ms and a precision of around 13.80 ms, depending on gait and hoof. For hoof-off detection, the acceleration algorithm was the most accurate with an accuracy of 3.20 ms and precision of 6.39 ms, independent of gait and hoof. These algorithms look highly promising for gait classification purposes although the applicability of these algorithms should be investigated under different circumstances, such as different surfaces and different hoof trimming conditions.
Ämnesord
- LANTBRUKSVETENSKAPER -- Veterinärmedicin -- Medicinsk biovetenskap (hsv//swe)
- AGRICULTURAL SCIENCES -- Veterinary Science -- Medical Bioscience (hsv//eng)
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- art (ämneskategori)
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